def test_perceptron(): iris = DataSet(name="iris") iris.classes_to_numbers() classes_number = len(iris.values[iris.target]) perceptron = PerceptronLearner(iris) tests = [([5, 3, 1, 0.1], 0), ([6, 3, 4, 1.1], 1), ([7.5, 4, 6, 2], 2)] assert grade_learner(perceptron, tests) >= 2
def test_neural_network_learner(): iris = DataSet(name="iris") classes = ["setosa", "versicolor", "virginica"] iris.classes_to_numbers(classes) nNL = NeuralNetLearner(iris, [5], 0.15, 75) tests = [([5, 3, 1, 0.1], 0), ([6, 3, 3, 1.5], 1), ([7.5, 4, 6, 2], 2)] assert grade_learner(nNL, tests) >= 2
def test_neural_network_learner(): iris = DataSet(name="iris") classes = ["setosa","versicolor","virginica"] iris.classes_to_numbers(classes) nNL = NeuralNetLearner(iris, [5], 0.15, 75) tests = [([5, 3, 1, 0.1], 0), ([5, 3.5, 1, 0], 0), ([6, 3, 4, 1.1], 1), ([6, 2, 3.5, 1], 1), ([7.5, 4, 6, 2], 2), ([7, 3, 6, 2.5], 2)] assert grade_learner(nNL, tests) >= 2/3 assert err_ratio(nNL, iris) < 0.25
def test_perceptron(): iris = DataSet(name="iris") iris.classes_to_numbers() classes_number = len(iris.values[iris.target]) perceptron = PerceptronLearner(iris) tests = [([5, 3, 1, 0.1], 0), ([5, 3.5, 1, 0], 0), ([6, 3, 4, 1.1], 1), ([6, 2, 3.5, 1], 1), ([7.5, 4, 6, 2], 2), ([7, 3, 6, 2.5], 2)] assert grade_learner(perceptron, tests) > 1/2 assert err_ratio(perceptron, iris) < 0.4